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Analyzing online forums to identify information needs and knowledge gaps in patients with left ventricular assist devices: a qualitative study.
Abdelhadi, Nasra; Klein, Stav; Shahar, Moni; Melnikov, Semyon.
Afiliação
  • Abdelhadi N; Nursing Department, Tel Aviv University, Israel.
  • Klein S; The Center for AI and Data Science, Tel Aviv University, Israel.
  • Shahar M; The Center for AI and Data Science, Tel Aviv University, Israel.
  • Melnikov S; Nursing Department, Tel Aviv University, Israel.
Article em En | MEDLINE | ID: mdl-38888980
ABSTRACT

AIM:

To explore the knowledge and unmet informational needs of candidates for left ventricular assist devices (LVADs), as well as of patients, caregivers, and family members, by analyzing social media data from the MyLVAD.com website. METHODS AND

RESULTS:

A qualitative content analysis method was employed, systematically examining and categorizing forum posts and comments published on the MyLVAD.com website from March 2015 to February 2023. The data was collected using an automated script to retrieve threads from MyLVAD.com, focusing on genuine questions reflecting information and knowledge gaps. The study received approval from an ethics committee. The research team developed and continuously updated categorization matrices to organize information into categories and subcategories systematically. From 856 posts and comments analyzed, 435 contained questions representing informational needs, of which six main categories were identified clothing, complications/adverse effects, LVAD pros and cons, self-care, therapy, and recent LVAD implantation. The self-care category, which includes managing the driveline site and understanding equipment functionality, was the most prominent, reflecting nearly half of the questions. Other significant areas of inquiry included complications/adverse effects and the pros and cons of LVAD.

CONCLUSION:

The analysis of social media data from MyLVAD.com reveals significant unmet informational needs among LVAD candidates, patients, and their support networks. Unlike traditional data, this social media-based research provides an unbiased view of patient conversations, offering valuable insights into their real-world concerns and knowledge gaps. The findings underscore the importance of tailored educational resources to address these unmet needs, potentially enhancing LVAD patient care.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article